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Affiliations
Pria Adi Saputra
Program Studi Pendidikan Dasar Pascasarjana UNNES
Sigit Saptono
Universitas Negeri Semarang
Joko Sutarto
Universitas Negeri Semarang
How to Cite
Application of Distance Learning to Suppress the Spread of COVID-19 in Public Elementary School Grogolbeningsari Kebumen Regency
Vol 10 No 4 (2021): December 2021
Submitted: Jul 27, 2021
Published: Dec 30, 2021
Abstract
Distance learning is not a new alternative in the world of education, but this model is back in popularity due to the Covid-19 pandemic. There is still very little literature on the implementation of learning during the pandemic so that it attracts the attention of researchers to analyze and describe the implementation of distance learning during the Covid-19 pandemic at Public Elementary School Grogolbeningsari to suppress the spread of the Covid-19 outbreak. The method used in this research is descriptive qualitative with data analysis techniques, in the form of triangulation combining the results of observations, interviews, and documentation. The sample in this study was seven respondents at Public Elementary School Grogolbeningsari. The results showed that (1) Planning, schools review and readjust curriculum 2013, improve teacher quality, fulfill facilities and infrastructure, complete documents, and innovate to develop strategies applied during the pandemic. (2) Implementation, although learning is switching to online and offline, teachers must quickly adjust to the pandemic, and they are required to be able to master various platforms such as WhatsApp, Google Form, YouTube, Zoom, and Television Broadcasting which they can use to fulfill students' learning rights and provide meaningful learning experiences. (3) Evaluation, the teacher can give WhatsApp feedback in daily activities, but the school still uses written assessments in the Mid-Semester and End Semester Assessments. Education has faced many challenges during the pandemic. Therefore, a collaboration between school members is very influential on the success of distance learning.